Matthias CaroLink opens in a new windowLink opens in a new window (Caltech)

Title: Quantum Computing Meets Machine Learning - A Math/TCS Perspective

Abstract: Machine learning, based on computational and statistical learning theory, constitutes a recent example of how influential applications arise from theoretical innovation. Quantum computing, rooted in quantum information theory, promises to be a future instance of the same phenomenon, providing a new paradigm of computation using features of quantum physics. In this talk, I will give an introduction to the theories underlying machine learning and quantum computing, and I will present recent developments at the intersection of the two fields. I will discuss machine learning models based on trainable quantum circuits, quantum extensions of computational learning theory, and learning from data collected in quantum experiments.